The present disclosure relates to a method of providing a lithography model, and particularly to a method of calibrating a sub-resolution assist feature (SRAF) printing model.
Images printed on a photoresist for an isolated lithographic pattern are more sensitive to focus variations than images for a dense lithographic pattern. Focus-exposure matrix (FEM) curves are thus more isofocal for dense lithographic patterns. Hence, dense lithographic patterns can be printed with a critical dimension (CD) that remains within tolerances for a broader range of defocus conditions.
Sub-resolution assist features (SRAFs) are added to mask shapes to create a denser environment for robust printing of main features. The SRAFs are not intended to be reproduced as distinct features in the photoresist, but they influence and modify the exact shape with which the main features are printed in the photoresist in the presence of the SRAFs relative to shapes that would be printed in the absence of the SRAFs. In order to avoid direct printing of the SRAFs, the size and location of the SRAFs need to be carefully optimized. If properly optimized, the SRAFs can provide benefit to the process performance of the lithographic process, for example, by increasing the depth of focus or process window, while avoiding direct printing of the SRAFs as separate but unintended patterns that could transfer to subsequent steps of the chip manufacturing process.
SRAFs are commonly used in lithography masks to improve the printability and process window of critical features. The SRAFs are placed as part of an overall data preparation program that includes a model based optical proximity correction (OPC) algorithm for all incoming design patterns that are placed on a lithographic mask. SRAFs are very challenging to model accurately because by nature the SRAFs are designed not to generate a directly corresponding pattern in a photoresist layer. An accurate SRAF model is supposed to correctly predict the effects that the SRAFs have on the main feature(s) including any shift in the best focus, and any undesirable printing of direct images of the SRAFs at the top, or the bottom, of the photoresist.
The process models used to implement the OPC algorithms are two-dimensional in nature, in that the process models only predict the shapes of printed features at a specific height (typically the bottom) in the photoresist or substrate. Typically, clear SRAF printing tends to occur at the top of the photoresist layer, and will not be detected by a process model calibrated to only predict printing at the bottom of the photoresist layer. In contrast, dark SRAF printing tends to occur at the bottom of the photoresist layer, and the calibrated resist threshold for showing presence of the dark SRAF printing might be set too high to detect the dark SRAF printing at the first sign of physical manifestation in the lithographically exposed and developed photoresist layer.
One solution to this problem is to set the exposure dose much higher (for clear SRAFs), or lower (for dark SRAFs), than the nominal dose to exaggerate the optical effects of the SRAFs on the photoresist layer. However, this strategy does not typically detect all instances of SRAF printing, and the change in main feature printing may obscure the SRAF printing behavior. Another solution is to use a full three-dimensional model of the photoresist layer, but three-dimensional models tend to require excessive computing, and thus, not suitable for manufacturing purposes. Further, the three-dimensional models also require additional calibration separate from the calibration of the two-dimensional models, and can result in inconsistent predictions if not properly calibrated. A third solution is to calibrate a separate two-dimensional model that is tuned to predict SRAF printing while sacrificing main feature prediction accuracy. These models are difficult to calibrate since such models must predict both printing and absence of printing, while the input data can only include the former.
Another challenge with modeling SRAFs is that the small size of the SRAFs can lead to inaccurate optical simulations when using the thin mask approximation (TMA), in which the mask absorber is assumed to be infinitely thin. This approximation speeds computation time but the approximation starts to break down as the width of the feature starts to approach the thickness of the absorber. The so-called electromagnetic field (EMF) effects introduce transmission and phase offsets into the optics. The EMF effects can cause the best focus of the main feature to shift depending on the placement and tone of the SRAFs.